Microsoft has 521 active AI-related job listings. The majority of these roles are focused on agents, representing 37% of the total, followed by application and serving infrastructure. Engineering is the most frequent function, with a significant number of openings, and the United States is the primary hiring country. Frequent tech tags include agent orchestration, model serving, and LLM observability, suggesting a focus on operationalizing AI models. Over the last 30 days, Microsoft has added 280 new AI roles, a 157% increase compared to the previous 30-day period.
Currently tracking 250 active AI roles, down 24% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$331k (avg $195k).
Microsoft currently has 343 active AI-related roles in our index. The most common open titles are: Principal Software Engineer (19), Senior Software Engineer (19), Software Engineer II (8), Principal Applied Scientist (7), Principal Data Scientist (4). Most positions are in Engineering and Research.
Microsoft's active AI hiring is concentrated in: agents (36%), application (21%), serving infrastructure (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Microsoft is hiring AI talent in: United States (308 roles), Canada (15 roles), Japan (8 roles), United Kingdom (7 roles).
Job postings at Microsoft most frequently mention: Computer Architecture, Python, Machine Learning, C#, C++.
In the past 30 days, Microsoft has posted 227 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Software Engineer II Software Engineer II role focused on building and scaling backend services for Microsoft AI Search Places, which uses geospatial knowledge and AI for location search. The role involves applying ML solutions to geospatial problems and experimenting with LLMs to improve system quality and efficiency. | Serve | 5 |
| Senior Software Engineer Senior Software Engineer on the Bing Multimedia team, focusing on building and evolving large-scale offline infrastructure for image and video search. The role involves designing, building, and operating scalable platforms that process vast amounts of data, with a strong emphasis on engineering metrics like latency, cost, availability, and quality. The team leverages state-of-the-art ML models and AI-assisted engineering practices to deliver world-class visual search experiences. | Serve |
| 5 |
| Senior Software Engineer Senior Software Engineer on the Surface Devices team responsible for designing, scaling, and maintaining CI/CD infrastructure for Windows OEM factory images. The role involves integrating Azure AI capabilities for intelligent log analysis, anomaly detection, and automation within the DevOps ecosystem. | Serve | 5 |
| Principal Software Engineer Principal Software Engineer to design, build, and operate core compute platform services for developers, enabling them to host and run various apps including AI Agent Apps at cloud scale. The role requires end-to-end technical leadership, hands-on component design and coding, and mentoring others on engineering and site reliability practices, with a focus on AI as a core building block. | Serve | 5 |
| Principal Software Engineer - CoreAI Principal Software Engineer for Microsoft's CoreAI Growth and Data Science team, focusing on data and analytics architecture, large-scale data pipelines, and leveraging AI to optimize workflows. The role involves cross-team collaboration, mentoring, and ensuring data governance and trust for AI workloads within the developer ecosystem. | Serve | 5 |
| Consultant A2 - Infra This role focuses on designing, building, and optimizing end-to-end cloud and on-premises infrastructure solutions, with a significant emphasis on supporting AI/ML workloads. The consultant will leverage Azure AI Services, containerized AI workloads, and integrate models into cloud environments, acting as a full-stack infrastructure consultant. | Serve | 5 |
| Sr Consultant - Infra Sr. Consultant focused on designing, building, and optimizing cloud and on-premises infrastructure solutions, with a specific emphasis on AI workloads. This role requires expertise in Azure AI Services, integrating frontier models, and managing AI developer tools as infrastructure components. The consultant will ensure secure, scalable, and high-performing environments for AI applications. | Serve | 5 |
| Principal Software Engineer Principal Software Engineer role focused on leading the architecture, design, and implementation of high-scale, low-latency services with an AI First approach within Microsoft's Identity engineering team. The role involves driving AI/ML-based engineering solutions, cloud environments (Azure), and large distributed systems, with a strong emphasis on security and reliability. | Serve | 5 |
| Software Engineer II Software Engineer II role focused on designing, developing, and optimizing networking infrastructure for large-scale AI training and inference in Azure Cloud. The role involves ensuring high performance, low latency, and minimal jitter for distributed AI workloads, working with cutting-edge networking hardware and software. | Serve | 5 |
| Senior Software Engineer- CTJ - Poly Senior Software Engineer to deliver secure, scalable, and mission critical AI infrastructure for Microsoft’s sensitive cloud environments, focusing on foundational services for Azure Machine Learning, Azure AI Services, Azure OpenAI, and Microsoft Foundry. The role involves building and operating AI native full stack systems, leveraging modern tooling and AI systems to accelerate development and enhance product quality within air gapped, sovereign, and commercial clouds. | Serve | 5 |
| Member of Technical Staff - Backend Engineer Backend Engineer for Microsoft Copilot, focusing on building and scaling the core backend platform including Orchestrator, Inference, and APIs to power AI-driven consumer experiences. The role involves developing secure, performant APIs, collaborating with cross-functional teams, and shipping high-quality code in a fast-paced environment. | ServeAgent | 5 |
| MTS - Site Reliability Engineer This role is for a Site Reliability Engineer (SRE) focused on ensuring the reliability, availability, and efficiency of large-scale distributed AI infrastructure. The SRE will work with ML researchers, data engineers, and product developers to operate platforms for training, fine-tuning, and serving generative AI models. Key responsibilities include maintaining uptime, designing observability systems, optimizing performance, building automation for deployments and incident response, and ensuring security and compliance in hybrid cloud/on-prem CPU+GPU environments. The role requires strong experience in SRE/DevOps, Kubernetes, CI/CD, public cloud platforms, monitoring tools, and programming languages like Python or Go, with a preference for experience with large-scale GPU clusters and HPC. | Serve | 5 |
| Research Intern - Azure Storage Research intern role focused on optimizing storage systems for AI workloads, including training, checkpointing, and inferencing. The role involves working with leading-edge AI customers to gain insights into their needs. | Serve | 5 |
| Software Engineer II Software Engineer II role focused on designing and building next-generation networking infrastructure for large-scale AI training and inference in Azure Cloud. The role involves developing high-performance, low-latency, and reliable networking capabilities to support distributed AI workloads, working at the intersection of AI and high-performance computing. | Serve | 5 |
| Member of Technical Staff, Hardware Health - MAI Superintelligence Team This role focuses on ensuring the reliability, performance, and availability of large-scale AI training infrastructures, specifically GPU clusters. It involves designing and developing hardware health monitoring and diagnostic frameworks, building predictive analytics pipelines using telemetry data, and leading incident triage for hardware anomalies. The goal is to drive automation in health management and partner with cross-functional teams to improve hardware design for reliability. | Serve | 5 |